from tensorflow import keras

# 229,229,3 => 8,8,2048
# 520,520,3 => 14,14,2048
# 448 => 12
SIDE = 448
IMG_SHAPE = (SIDE, SIDE, 3)

# Create the base model from the pre-trained model MobileNet V2
base_model = keras.applications.InceptionV3(input_shape=IMG_SHAPE,
# We cannot use the top classification layer of the pre-trained model as it contains 1000 classes.
# It also restricts our input dimensions to that which this model is trained on (default: 299x299)
                                               include_top=False,
                                               weights='imagenet')

base_model.summary(line_length=120)
